如果你关心 AI 如何影响公共讨论或做社交平台产品，这篇论文揭示了 AI 改写功能可能无意中操纵舆论的机制，值得一读。
一项新研究通过实证和理论分析发现，大型语言模型（如 GPT 系列、Grok）在编辑人类关于争议话题的帖子时，会引入方向性偏见，例如倾向于支持枪支管控、反对无神论。研究进一步建立数学模型，证明这种偏见在社交网络中通过 AI 中介的沟通会被放大，从而改变集体舆论。作者还审计了 X 平台的“解释此帖”功能，发现 Grok 在堕胎相关内容上存在“支持生命”偏见，并追溯到具体设计选择。该研究对欧盟等地的 AI 监管立法具有重要参考意义。
AI-Mediated Communication Can Steer Collective Opinion
Generative artificial intelligence (AI) is increasingly integrated into the online platforms where humans exchange opinions; large language models (LLMs) now polish users' posts on LinkedIn and provide context for content shared on X. While prior work has shown that AI can express biased opinions and shape individuals' opinions during human-AI interactions, less attention has been paid to its influence on collective opinion formation when mediating human-to-human communication. We address this gap via a combination of empirical and theoretical analyses. We show empirically that LLMs from multiple popular families introduce directional biases when instructed to edit human-written texts on contested topics, for example, nudging texts in favor of gun control and against atheism. Building on this observation, we introduce a mathematical model of opinion dynamics in which an AI system sits between users on a social network, transforming the opinions they express and perceive. By analytically characterizing the equilibrium of this model and performing simulations on real social network data, we show that biases introduced by AI in human-to-human communication can be amplified through the network and shift collective opinion in their direction. In light of these findings, we investigate whether such biases are controllable by online platforms. We audit the "Explain this post" feature on X and find evidence of pro-life bias in Grok's outputs on abortion-related content, which we trace back to specific design choices. We conclude with a discussion of the broader implications of our findings in relation to ongoing legislative efforts in the European Union.